The study of individual normative cephalometric parameters in individuals of different sexes and ages is important for the "Cephalometrics for orthognathic surgery method", as it allows to accurately diagnose abnormalities and develop personalized treatment plans. This contributes to achieving better aesthetic results, reducing the risk of complications and increasing the effectiveness of surgical interventions. Taking into account age, sex, and face type helps predict long-term changes and adapt the treatment plan to obtain optimal results. In addition, it improves assessment accuracy and standardizes evidence-based approaches, making it easier to compare results between clinics. Thus, individual regulatory parameters are key to successful orthognathic surgery. The purpose of the study is to build and analyze regression models of teleroentgenometric indicators using the "Cephalometrics for orthognathic surgery" method in Ukrainian young women with a wide face type. 25 Ukrainian young women with an orthognathic bite and a wide face type underwent a cephalometric study using the "Cephalometrics for orthognathic surgery" (COGS-method) method. For the correct modeling of cephalometric parameters, their division into three groups was applied (Dmitriev M. O., 2016, 2017): the first group – basic metric characteristics of the skull; the second group – teleroentgenometric indicators by which it is possible to change the parameters of the upper and lower jaws with the help of orthognathic surgery; the third group – indicators that characterize the position of each tooth relative to each other, cranial structures and the profile of the soft tissues of the face. Construction of regression models was carried out in the license package "Statistica 6.0". Only reliable models with a coefficient of determination R2 of at least 0.60 were subject to further analysis. It was found that in young women with a wide face, using the COGS method, 6 models of teleroentgenometric indicators were built out of 33 possible, which were included in the second and third groups depending on the indicators of the first group (R²= from 0.601 to 0.705, p<0.01-0.001); out of 19 possible, 16 indicator models were built, which were included in the third group depending on the indicators of the first and second groups (R²= from 0.614 to 0.983, p<0.01-0.001). The analysis of the models showed that most often the regression equations of the indicators included in the second and third groups, depending on the indicators of the first group, include the distance P-PTV and N-СС according to Ricketts, N-Se according to Schwarz, N-S and S-Ar according to Roth-Jarabak, Ar-Pt and Pt-N according to the COGS method (7.69 % each), as well as the value of the H angles according to Schwarz and N-S-Ba according to Bjork; and to the indicator models that were included in the third group depending on the indicators of the first and second groups – the value of the distances ANS-Me, N-B, N-A, N-Pog, B-Pog, N-CC according to Ricketts, PNS-N, Ar-Go and ANS-PNS, as well as the magnitude of the angles N-A-Pog, N-S-Ba according to Bjork, MP-HP, as well as Por-NBa according to Ricketts.
